Title: Intelligent reflecting surfaces for cognitive radio networks

Authors: Raed Alhamad

Addresses: Information Technology Department, Saudi Electronic University, Kingdom of Saudi Arabia

Abstract: In this paper, we derive the secondary throughput of cognitive radio networks with energy harvesting and adaptive transmit power. Intelligent reflecting surfaces (IRS) with N reflectors are deployed as a transmitter or a reflector so that all reflections are in phase at secondary destination. The analysis is performed in the absence or presence of interference from primary source. IRS with N = 128 reflectors offers 6, 12, 18, 24 dB gain with respect to N = 64, 32, 16, 8. When the number of reflectors is doubled, we obtain 6 dB gain in throughput. IRS allow 25, 31, 38 and 44 dB gain with respect to the absence of IRS for a number of reflectors N = 8, 16, 32, 64. IRS deployed as a transmitter improves the throughput by 1 dB with respect to IRS deployed as a reflector. We also consider the use of multiple antennas at the secondary destination and evaluate packets' waiting time and total delay.

Keywords: intelligent reflecting surfaces; IRS; 6G; cognitive radio networks.

DOI: 10.1504/IJAHUC.2023.129389

International Journal of Ad Hoc and Ubiquitous Computing, 2023 Vol.42 No.3, pp.148 - 157

Received: 07 Jul 2021
Accepted: 06 Apr 2022
Published online: 07 Mar 2023 *

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